Many people are pricking up their ears and starting to take an interest in the various benefits of big data analytics, as it becomes increasingly clear that businesses simply can’t do without this in-depth information.
One area in which big data is assuming a major role is in management. Why? Because this type of technology makes it possible for businesses to analyse the numbers and work out how they can continue to grow and prosper – even if they have limited budgets.
ComputerWorld has pointed out that this type of managerial approach is, in part, being adopted thanks to the real-life story of a US baseball team whose manager was able to turn around its fortunes, despite its lack of money. They were able to analyse statistics and then come up with the most cost-effective player roster in the league.
Data transformed the way US baseball teams are managed
Big data’s analytical power is generally spoken of when talking about its ability to improve efficiency and generally do what it is supposed to do – namely handle ever-increasing volumes of information for a variety of businesses.
However, this Forbes report illustrates the way in which online auction house eBay managed to take the concept of big data and apply it in an unusual way in order to save itself significant sums. At EMC, we think that this type of thinking is the new normal. The unusual becomes the usual.
Tens of millions of customers around the world and an incredibly complex infrastructure of online services mean that eBay is generally required to manage huge volumes of data on a daily basis. However, it also needs a significant IT infrastructure made up of various hardware components housed in disparate locations, all of which pull together towards a common goal. But this also costs the company significant sums of money (and significant means more money than you might imagine).
In the recent past, eBay decided to turn its knowledge of big data analytics on to this IT infrastructure itself and pulled information from every single asset and component, so that it could see which areas were operating efficiently and which servers might not be making best use of their resources and being exploited to the fullest extent.
Data scientists and business analysts: are they one and the same, or are they worlds apart? If the analogy that a data scientist is a business analyst working in California is to be believed, then the positions are only separated by a zeitgeist job title. But in reality, this isn’t the case: the two roles have very different parts to play in the ever-evolving landscape of big data. While data scientists are (and will continue to be) eagerly sought after in an attempt to plug a gaping hole in the employment market, business analysts are already there — on the ground, working with the data harvested by their enterprises. More and more as the industry progresses forward, these business analysts will be called on to contextualise that data, providing valuable business and industry insights.
Big data is sweeping into every part of the business world. According to the IDC’s Digital Universe Study, the amount of information managed by enterprise centres will grow by 50 times in this decade alone. And, as big data pervades the business world, traditional models will change to incorporate it and traditional job roles will change as part of a cultural disruption. The smart business analysts – those who wish to be change agents and seen as integral to their business and industry – will be at the forefront of this shift. So, with that in mind, we’ve put together a primer for business analysts — something that you can cut-out-and-keep, or pass on to your colleagues. Open up the primer below.
I was fascinated to read recently that analysts at Gartner have reported on the nature of hype in the IT market. (Yes, my plane journey was that dull.) They looked specifically at cloud computing and the various technologies and services that are related to it.
Researchers have actually developed a life cycle which reflects the current state of particular buzzwords, such as big data and the cloud, and then considers which point on the scale a technology has reached and what the future might hold for it.
Big Data and the Cloud: Should You Believe the Hype?
At the moment, Gartner believes that big data is one of the most heavily publicised and talked-about technologies, both in terms of expectations and what it can actually deliver. So that’s reassuring, since I work in that field.
Interestingly, if big data follows the standard life cycle then this peak will followed by a trough, during which time expectations are adjusted and realities assessed as businesses and users acclimatise to the actual capabilities of a previously over-hyped platform or service. Don’t believe me? Well, think back to the great dreams of Java (write once, deploy everywhere – remember that?)
How do you begin to prepare your organisation to work with big data? IT leaders are constantly told by the industry press that they need to start using the valuable predictive insights that can be gained from large, multi-structured datasets. The problem is, there usually isn’t any information on how to actually get started.
Let’s change that right now. There’s no doubt that you do need to get going with a big data strategy – a 2011 IDC study claims that the amount of information managed by enterprise data centres will increasing by 50 times. You need to be prepared to handle this data and benefit from it. If you’re not thinking about a big data strategy, you’re competitors probably are: a May 2012 study by CIO Magazine, conducted on behalf of EMC, found that 54% of organisation are already putting together a big data strategy.
How do you put your strategy together? The most important part is to take account of the factors that are specific to your organisation. Which teams might benefit the most from big data insights? A large part of setting a big data strategy in motion is getting key stakeholders within your organisation involved, sharing your successes with the skeptical to build support, and picking your battles carefully. The last thing you want to do is be seen as a threat to other departments, a sort of ‘data police’ for your organisation. That’s a surefire way to make sure that no one else in your organisation will support you. And with major benefits on the line, you can’t afford to lose support. Be prepared for organisational politics and show everyone how a big data strategy can help them all.
That’s just one facet of putting a big data strategy in place, but it’s an aspect that is often overlooked. For more on how to prepare your organisation for a big data strategy, both culturally and operationally, take a look at ‘Big Data is Talking. Are You Listening?’, an interactive white paper from EMC.